Testing mediation in nursing research: Beyond baron and kenny

Nursing Research

Volumn 59, Issue 4, 2010, Pages 288-294

  Krause, Melanie R ^a   Serlin, Ronald C ^b   Ward, Sandra E ^a   Rony, Yaffa Zisk ^b   Ezenwa, Miriam O ^a   Naab, Florence ^c  

^a School Nursing   (United States)

^b Department of Educational Psychology ^*  (United Kingdom)

^c UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

data analysis statistical; data interpretation statistical; mediation; models statistical

Indexed keywords

ARTICLE; EPIDEMIOLOGY; EQUIPMENT; HUMAN; METHODOLOGY; MONTE CARLO METHOD; NONPARAMETRIC TEST; NURSING RESEARCH; REPRODUCIBILITY; STANDARD; STATISTICAL ANALYSIS; STATISTICAL MODEL;

BIAS (EPIDEMIOLOGY); DATA INTERPRETATION, STATISTICAL; EFFECT MODIFIERS (EPIDEMIOLOGY); HUMANS; MODELS, STATISTICAL; MONTE CARLO METHOD; NURSING RESEARCH; REPRODUCIBILITY OF RESULTS; RESEARCH DESIGN; STATISTICS, NONPARAMETRIC;

EID: 77954244125     PISSN: 00296562     EISSN: None     Source Type: Journal    
DOI: 10.1097/NNR.0b013e3181dd26b3     Document Type: Article

References (37)

1. Aroian, L. A. (1944). The probability function of the product of two normally distributed variables. Annals of Mathematical Statistics, 18, 265-270.
2. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
3. Bennett, J. A. (2000). Mediator and moderator variables in nursing research: Conceptual and statistical differences. Research in Nursing & Health, 23(5), 415-420.
4. Bobko, P., & Rieck, A. (1980). Large sample estimators for standard errors of functions of correlation coefficients. Applied Psychological Measurement, 4(3), 385-398.
5. Bollen, K. A., & Stine, R. (1990). Direct and indirect effects: Classical and bootstrap estimates of variability. Sociological Methodology, 20, 115-140.
6. Bradley, J. V. (1978). Robustness? British Journal of Mathematical and Statistical Psychology, 31, 144-152.
7. Bradley, J. V. (1980). Nonrobustness in Z, t, and F tests at large sample sizes. Bulletin of the Psychonomic Society, 16(5), 333-336.
8. Cheung, G. W., & Lau, R. S. (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11(2), 296-325.
9. Clogg, C. C., Petkova, E., & Shihadeh, E. S. (1992). Statistical methods for analyzing collapsibility in regression models. Journal of Educational Statistics, 17(1), 51-74.
10. 2 test of goodness of fit. Annals of Mathematical Statistics, 23, 315-345.
11. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159.
12. Cohen, J., & Cohen, P. (1983). Applied multiple regression/ correlation analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum.
13. Collins, L. M., Graham, J. J., & Flaherty, B. P. (1998). An alternative framework for defining mediation. Multivariate Behavioral Research, 33(2), 295-312.
14. Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7, 1-26.
15. Efron, G., & Tibshirani, R. (1993). An introduction to the bootstrap. New York: Champan & Hall/CRC.
16. Freedman, L. S., & Schatzkin, A. (1992). Sample size for studying intermediate endpoints within intervention trials or observational studies. American Journal of Epidemiology, 136(9), 1148-1159.
17. Goodman, L. A. (1960). On the exact variance of products. Journal of the American Statistical Association, 55, 708-713.
18. Judd, C. M., & Kenny, D. A. (1981a). Estimating the effects of social interventions. Cambridge, England: Cambridge University Press.
19. Judd, C. M., & Kenny, D. A. (1981b). Process analysis: Estimating mediation in treatment evaluations. Evaluation Review, 5(5), 602-619.
20. Kenny, D. A. (2008). Mediation. Retrieved February 4, 2009, from http://davidakenny.net/cm/mediate.htm
21. Lindley, P., & Walker, S. (1993). Theoretical and methodological differentiation of moderation and mediation. Nursing Research, 42(5), 276-279.
22. MacKinnon, D. P., & Lockwood, C. (2001). Distribution of products tests for the mediated effect. Unpublished manuscript.
23. MacKinnon, D. P., Lockwood, C., & Hoffman, J. (1998, June). A new method to test for mediation. Paper presented at the annual meeting of the Society for Prevention Research, Park City, UT.
24. MacKinnon, D. P., Lockwood, C. M., Hoffmann, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test the significance of mediation and other intervening variable effects. Psychological Methods, 7(1), 83-104.
25. MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99-128.
26. McGuigan, K., & Langholtz, B. (1988). A note on testing mediation paths using ordinary least-squares regression. Unpublished manuscript.
27. Olkin, I., & Finn, J. D. (1995). Correlation redux. Psychological Bulletin, 118, 155-164.
28. Pearson, E. S. (1929). The distribution of frequency constants in small samples from non-normal symmetrical and skew populations. Biometrika, 12, 259-285.
29. Quenouille, M. (1956). Notes on bias in estimation. Biometrika, 43, 353-360.
30. Serlin, R. C. (2000). Testing for robustness in Monte Carlo studies. Psychological Methods, 5(2), 230-240.
31. Serlin, R. C., Jacobs, V., & Franke, T. (1995, April). Testing for mediation. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA.
32. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental design for generalized causal inference. Boston: Houghton-Mifflin.
33. Sheets, V. L., & Braver, S. L. (1999). Organizational status and perceived sexual harassment: Detecting the mediators of a null effect. Personality and Social Psychology Bulletin, 25(9), 1159-1171.
34. Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological Methods, 7(4), 422-445.
35. Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In S. Leinhardt (Ed.), Sociological methodology (pp. 290-312). Washington, DC: American Sociological Association.
36. Tukey, J. W. (1958). Bias and confidence in non-quite large samples. Annals of Mathematical Statistics, 29, 614.
37. Ward, S. E., Serlin, R. C., Donovan, H. S., Ameringer, S. W., Hughes, S., Pe-Romashko, K., et al. (2009). A randomized trial of a representational intervention for cancer pain: Does targeting the dyad make a difference? Health Psychology, 28(5), 588-597.